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Robust Vehicle Tracking Multi-feature Particle Filter

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Multimedia, Computer Graphics and Broadcasting (MulGraB 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 263))

Abstract

Object detection and tracking have been studied separately in most cases. Particle filtering has proven very successful for non-linear and non-Gaussian estimation problems. This paper presents a new method for tracking moving vehicles with temporal disappearance. The proposed method can continue tracking after disappearance. Color distribution of objects is integrated into particle filtering algorithm. As the color of an object can vary over time dependent on the illumination, a likelihood model is used including color cue and detection cue. Color cue is provided by using Bhattacharyya distance, and detection cue is provided by Euclidean distance. Tests are made by using highway cameras that are located on bridge.

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© 2011 Springer-Verlag Berlin Heidelberg

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Yildirim, M.E., Song, J., Park, J., Yoon, B.W., Yu, Y. (2011). Robust Vehicle Tracking Multi-feature Particle Filter. In: Kim, Th., et al. Multimedia, Computer Graphics and Broadcasting. MulGraB 2011. Communications in Computer and Information Science, vol 263. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27186-1_24

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  • DOI: https://doi.org/10.1007/978-3-642-27186-1_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27185-4

  • Online ISBN: 978-3-642-27186-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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